Using contrast patterns between true complexes and random subgraphs in PPI networks to predict unknown protein complexes

CORC > 天津工业生物技术研究所 > 结构生物信息学和整合系统生物学实验室宋江宁 > 期刊论文

	Using contrast patterns between true complexes and random subgraphs in PPI networks to predict unknown protein complexes
	Liu, Quanzhong 1; Song, Jiangning 2,3,4,5; Li, Jinyan 6,7,8
刊名	SCIENTIFIC REPORTS
	2016-02-12
卷号	6
英文摘要	Most protein complex detection methods utilize unsupervised techniques to cluster densely connected nodes in a protein-protein interaction (PPI) network, in spite of the fact that many true complexes are not dense subgraphs. Supervised methods have been proposed recently, but they do not answer why a group of proteins are predicted as a complex, and they have not investigated how to detect new complexes of one species by training the model on the PPI data of another species. We propose a novel supervised method to address these issues. The key idea is to discover emerging patterns (EPs), a type of contrast pattern, which can clearly distinguish true complexes from random subgraphs in a PPI network. An integrative score of EPs is defined to measure how likely a subgraph of proteins can form a complex. New complexes thus can grow from our seed proteins by iteratively updating this score. The performance of our method is tested on eight benchmark PPI datasets and compared with seven unsupervised methods, two supervised and one semi-supervised methods under five standards to assess the quality of the predicted complexes. The results show that in most cases our method achieved a better performance, sometimes significantly.
WOS标题词	Science & Technology
类目[WOS]	Multidisciplinary Sciences
研究领域[WOS]	Science & Technology - Other Topics
关键词[WOS]	GENE-EXPRESSION PROFILES ; SIGNALING NETWORK ; EMERGING PATTERNS ; SACCHAROMYCES-CEREVISIAE ; BIOLOGICAL NETWORKS ; CANCER ; IDENTIFICATION ; ALGORITHM ; DISCOVERY ; SCALE
收录类别	SCI
语种	英语
WOS记录号	WOS:000369930400001
内容类型	期刊论文
源URL	[http://124.16.173.210/handle/834782/1534]
专题	天津工业生物技术研究所_结构生物信息学和整合系统生物学实验室宋江宁_期刊论文
作者单位	1.Northwest A&F Univ, Coll Informat Engn, Yangling 712100, Peoples R China 2.Monash Univ, Monash Bioinformat Platform, Melbourne, Vic 3800, Australia 3.Monash Univ, Dept Biochem & Mol Biol, Melbourne, Vic 3800, Australia 4.Monash Univ, Monash Ctr Data Sci, Fac Informat Technol, Melbourne, Vic 3800, Australia 5.Chinese Acad Sci, Natl Engn Lab Ind Enzymes, Tianjin 300308, Peoples R China 6.Chinese Acad Sci, Key Lab Syst Microbial Biotechnol, Tianjin Inst Ind Biotechnol, Tianjin 300308, Peoples R China 7.Univ Technol Sydney, Adv Analyt Inst, Fac Engn & IT, Broadway, NSW 2007, Australia 8.Univ Technol Sydney, Ctr Hlth Technol, Fac Engn & IT, Broadway, NSW 2007, Australia
推荐引用方式 GB/T 7714	Liu, Quanzhong,Song, Jiangning,Li, Jinyan. Using contrast patterns between true complexes and random subgraphs in PPI networks to predict unknown protein complexes[J]. SCIENTIFIC REPORTS,2016,6.
APA	Liu, Quanzhong,Song, Jiangning,&Li, Jinyan.(2016).Using contrast patterns between true complexes and random subgraphs in PPI networks to predict unknown protein complexes.SCIENTIFIC REPORTS,6.
MLA	Liu, Quanzhong,et al."Using contrast patterns between true complexes and random subgraphs in PPI networks to predict unknown protein complexes".SCIENTIFIC REPORTS 6(2016).